Solving Business Problems with Statistics


Course Number: STAT-104

Duration: 3 days (19.5 hours)

Format: Live, hands-on

Statistics Training Overview

Accelebrate's Solving Business Problems with Statistics training course teaches participants how to apply appropriate statistical procedures and models to answer business questions and then effectively communicate impact to stakeholders.

Location and Pricing

Accelebrate offers instructor-led enterprise training for groups of 3 or more online or at your site. Most Accelebrate classes can be flexibly scheduled for your group, including delivery in half-day segments across a week or set of weeks. To receive a customized proposal and price quote for private corporate training on-site or online, please contact us.

Objectives

Students will leave the course able to use Excel to build statistical models that answer questions such as:

  • What's the relationship between a variable and an outcome?
  • If I adjust X, what will be the impact on Y?  Are there natural limits I should be aware of?
  • What's coming next?  Are we going up or down and by how much?
  • Why are we going up or down?  How impactful is each variable?  (In other words, what should I focus on first?)
  • Are there any unusual outliers?  What caused those?  Do I need to do something about this?
  • How likely is any given idea or decision or campaign to be successful? (i.e., logistic regression)
  • Did any given change or decision make a material business impact?

Prerequisites

Students have access to Microsoft Excel and are familiar with writing calculations and formulas within Excel.

Outline

Expand All | Collapse All

Introduction
Why Use Statistics?
Installing the Data Analysis Tool Pack add-in for Excel
Exploring and Visualizing Data
  • Types of variables and how to visualize each
Descriptive Statistics
  • Uses for specific measures and how to visualize
    • Samples vs. populations
    • Confidence Intervals
    • Average, median, standard deviation, quartiles & percentiles
    • Looking at the shape of the data and the impact of outliers
    • Cautions and common pitfalls (e.g. Anscombe’s Quartet)
  • Dealing with bad data and ensuring it’s reliable for good decisions
Overview of Probability
Method for Creating Predictive Models
How to Choose an Appropriate Model
Regression
  • Correlation
  • Linear Regression
    • When to use it
    • How to interpret meaningfully
    • For nonlinear data
  • Multivariate
Logistic Regression
ANOVA
  • t-Test
  • One-Way ANOVA
  • Two-Way ANOVA
Chi-Square 
Time Series & Forecasting
Conclusion

Training Materials:

All students receive comprehensive courseware.

Software Requirements:

  • Microsoft Excel 2010 or later (2013 or later recommended) with the latest update installed
  • Internet access
  • Related data and lab files that Accelebrate would provide


Learn faster

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Satisfaction guarantee

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